Color to Grayscale Conversion Based On Neighborhood Pixels Effect Approach for Digital Image

Conventional color to grayscale conversion algorithms cannot perform well in certain circumstances and the resultant grayscale images produced have low contrast and interpretability. Thus, we propose a new adaptive approach to overcome the drawback, namely the neighborhood pixels effect approach. In this approach two algorithms are proposed under this approach, namely the Neighborhood Effect Color to Grayscale (NECG) and Stretched Neighborhood Effect Color to Grayscale (SNECG) conversion algorithms. The experiment results show that the resultant grayscale images produced by the proposed algorithms have higher level of brightness, contrast, and amount of details revealed compared with those proposed by conventional methods. These promising findings suggest that the proposed algorithms are potentially useful for preand post-processing stages of digital images.